A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG

• Published in: PloS one Vol. 16; no. 6; p. e0253094
• Main Authors: Tawhid, Md. Nurul Ahad, Siuly, Siuly, Wang, Hua, Whittaker, Frank, Wang, Kate, Zhang, Yanchun
• Format: Journal Article
• Language: English
• Published: San Francisco Public Library of Science 25.06.2021; Public Library of Science (PLoS)
• Subjects: Accuracy; Artificial neural networks; Autism; Biology and Life Sciences; Biomarkers; Classification; Communication; Computer and Information Sciences; Datasets; Deep learning; Developmental disabilities; Diagnosis; EEG; Electroencephalography; Engineering and Technology; Evaluation; Feature extraction; Feature selection; Fourier analysis; Fourier transforms; Fractals; Learning algorithms; Machine learning; Magnetic resonance imaging; Medical imaging; Medicine and Health Sciences; Model accuracy; Neural networks; Neurological diseases; Physical Sciences; Principal components analysis; Research and Analysis Methods; Signal processing; Social factors; Social Sciences; Support vector machines; Temporal resolution; Wavelet transforms; Australia; Victoria Australia

Autism spectrum disorder (ASD) is a developmental disability characterized by persistent impairments in social interaction, speech and nonverbal communication, and restricted or repetitive behaviors. Currently Electroencephalography (EEG) is the most popular tool to inspect the existence of neurolog...